Automated utility meter reading system with variable bandwidth receiver

ABSTRACT

Methods and apparatus are disclosed for Automated Meter Reading (AMR) systems for determining quantities of a consumed utility product including electric, gas, and water service, using wireless data transfer. To compensate for the frequency drifts of the transmitters, these methods and apparatus, with minimum pre-processing of the received data, allow for on-the-fly adjustability of receiver bandwidth by merely changing a pre-calculated weighting function. As such, it is possible to use a fixed size Discrete Fourier Transform (DFT), or in particular a fixed N-point Fast Fourier Transform, for signals of different bandwidths.

TECHNICAL FIELD

The embodiments of the invention relate generally to an automated meterreading (AMR) system such as automated utility resource measurements,data collection, and exercise of control and notification, and moreparticularly to mobile or fixed AMR receivers for monitoring of utilityconsumption.

BACKGROUND

Historically the meter readings of the consumption of utility resourcessuch as water, gas, or electricity has been accomplished manually byhuman meter readers at the customers' premises. The relatively recentadvances in this area include collection of data by telephone lines,radio transmission, walk-by, or drive-by reading systems using radiocommunications between the meters and the meter reading devices.Although some of these methods require close physical proximity to themeters, they have become more desirable than the manual reading andrecording of the consumption levels. Over the last few years, there hasbeen a concerted effort to automate meter reading by installing fixednetworks that allow data to flow from the meter to a host computersystem without human intervention. These systems are referred to in theart as Automated Meter Reading (AMR) systems.

A mobile radio AMR system consists of three basic components: anEncoder-Receiver-Transmitter (ERT), a Data Collection Unit (DCU), andAMR Software. The ERT is a meter interface device attached to the meter,which either periodically transmits utility consumption data(“bubble-up” ERTs), or receives a “wake up” polling signal or a requestfor their meter information from a transceiver mounted in a passingvehicle or carried by the meter reader. The ERT, in response to awake-up signal, broadcasts the meter number, the meter reading, andother information to the DCU, which is a mobile computer in, forexample, the meter reading vehicle. The DCU collects the informationfrom the ERTs for subsequent uploading into the AMR Software system. TheAMR Software interfaces with the main system and updates the appropriateaccounts of the billing system with the new meter readings.

Today's ERT signals are not synthesized and drift in frequency due totemperature changes, location of the ERT modules with respect to theother objects, and internal heating and pulling. The frequency shifts,in turn, create problems for a narrowband receiver. As such, widebandreceivers are required to read ERTs, but wideband receivers are moreprone to unwanted interference and other problems. One of the possiblesolutions for this problem is to synthesize the ERT signals as widebandsignals. However, it is not possible to read a wideband ERT with anarrowband receiver.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates the basic elements and processes of a mobile AMRsystem.

FIG. 2 is a high level schematic diagram of the signal path within atypical AMR system.

FIG. 3 is a schematic diagram of the windowing, partitioning,overlaping, adding, and the FFT processing of the Weighted Overlap-Add(WOLA) method.

FIG. 4 is a schematic diagram of an application of four window functionsin accordance with an embodiment of the invention.

FIG. 5 is a flow diagram of the proposed method in accordance with anembodiment of the invention.

DETAILED DESCRIPTION

Embodiments of the present invention relates generally to an AMR systemsuch as automated utility resource measurements, data collection, andexercise of control and notification, and more particularly to AMRreceivers that are adjustable to accept signals of different bandwidths.In light of the fact that there is certainly a need for a receiver thatcan easily and efficiently change its bandwidth to accommodate differenttransmitters while keeping the computational requirements relativelyunchanged, the embodiments of this invention keep the signal processingcomputational requirements and complexity of the different bandwidthsrelatively constant. This is done by basic manipulation of the receiveddata prior to Discrete Fourier Transform (DFT) or, in particular, priorto Fast Fourier Transform (FFT) operations.

In the following description, several specific details are presented toprovide a thorough understanding of the embodiments of the invention.One skilled in the relevant art will recognize, however, that theinvention can be practiced without one or more of the specific details,or in combination with or with other components, etc. In otherinstances, well-known implementations or operations are not shown ordescribed in detail to avoid obscuring aspects of various embodiments ofthe invention.

The terminology used in the description presented below is intended tobe interpreted in its broadest reasonable manner, even though it isbeing used in conjunction with a detailed description of certainspecific embodiments of the invention. Certain terms may even beemphasized below; however, any terminology intended to be interpreted inany restricted manner will be overtly and specifically defined as suchin this Detailed Description section.

Reference throughout the specification to “one embodiment” or “anembodiment” means that a particular feature, structure, implementation,or characteristic described in connection with the embodiment isincluded in at least one embodiment of the present invention. Thus, usesof the phrases “in one embodiment” or “in an embodiment” in variousplaces throughout the specification are not necessarily all referring tothe same embodiment. Furthermore, the particular features, structures,implementation, or characteristics may be combined in any suitablemanner in one or more embodiments.

FIG. 1 illustrates the basic elements and processes of a typical mobileAMR system. As illustrated in FIG. 1, a passing data-collecting vehicle102 first sends a wake-up signal 104 to each ERT, such as ERT 106. Uponthe receipt of the wake-up call 104, each ERT transmits the requiredinformation 108, which is subsequently received by a DCU 110 of thepassing vehicle 102. Afterward, the received ERT signal goes throughseveral signal-processing steps and the embedded data is retrieved fromit. Finally, the retrieved data may be uploaded from the DCU 110 to amain system or computer 112 for billing and other purposes.

In general, if a receiver, such as the one included in the DCU 110,utilizes an N-point FFT to process a synthesized narrowband ERT signal,the same receiver may use an M×N-point FFT to process another ERT'ssignal with a bandwidth M times narrower. Alternatively, a receiver mayuse the same N-point FFT to merely process every K^(th) point of the FFToutput (where K is an integer multiple of 2), which is called“decimation” of the FFT.

FIG. 2 is a high level schematic diagram of a signal path within an AMRsystem. As depicted in FIG. 2, a receiver 202 portion of the DCU 110receives the ERT 106 transmitted signal 108. As part of the receivingprocess the received signal is passed through a low-noise amplifier LNAbefore Radio Frequency (RF) filtering of the signal. The gain of the RFfiltered signal will be subsequently controlled by passing it through anautomatic gain controller AGC, after which the signal goes through amixer and filtered again by an intermediate filter of 70 MHz. Thissignal is again amplified by an IF amplifier before being input to block204. After some pre-processing on the signal under block 204 (describedbelow), such as sampling, scaling, parsing, and combining, the resultingdata points go through some form of transformation such as under an FFT206. Subsequently, the transformed data is decoded and embeddedinformation is deciphered under block 208, to be later uploaded into themain system 112. In block 208, the digital signal processing (DSP) ofthe data comprises inputs from the channel correlator and an automaticgain controller, before the processed data becomes available on a serialport through a universal asynchronous receiver-transmitter UART.

Gumas, in his paper titled “Window-presum FFT achieves high-dynamicrange, resolution”, which is incorporated by reference, mathematicallyshows that the mere computation of every M^(th) point of an FFT outputcan be achieved by partitioning the M×N data points into M equal datagroups (where M is an integer multiple of 2), overlapping and addingthem together, and processing the resulting N data points by an N-pointFFT. Furthermore, prior to such partitioning, the wideband signal can bemultiplied by a Window function to scale different segments of itsspectrum. It is known to those skilled in the relevant arts that awindowed FFT serves as a filter bank of uniformly spaced and shapeddigital filters, and the window itself is the filters' impulse response.

FIG. 3 is a schematic diagram of the windowing, partitioning,overlapping, adding, and the FFT processing of the Weighted Overlap-Add(WOLA) method. In FIG. 3 the sampled data 302 is loaded into an inputbuffer 304. During the next step of the process, the data residing inthe buffer 304 is multiplied by a weighting function 306, whichrepresents the windowing process, to produce multiplied data 308.Subsequent to the multiplication of the buffer 304 data with theweighting function 306, the multiplied data 308 is partitioned into Mgroups of data, each having N-data points. Afterward, the M groups areall overlapped and all corresponding data points of all groups are addedtogether to form one resulting group with N-data points, 310. ThisN-data-point group resulting from the addition process, 310, will laterenter an N-point FFT (block 312) before being decoded (block 314).

Embodiments of the present invention take advantage of this mathematicalconcept to process a range of narrow to wideband signals by a fixedN-point FFT while the entire computation process remains the same forall bandwidths (except for the value of a multiplier). Each multiplieris a windowing function, which is pre-calculated and stored in a memory.Therefore, the embodiments can process the signals of various bandwidthsby performing the exact same operations except for using a differentmemory content in one of its steps. Therefore, with this method, a merechange of a multiplier adjusts the receiver bandwidth for receiving awider- or a narrower-band signal.

FIG. 4 is a schematic diagram of the application of four windowfunctions in accordance with an embodiment of the invention. In thisembodiment an input buffer 304 is used to hold 4N input data points atall times, regardless of the input signal bandwidth, while an N-pointFFT processes the data after it is multiplied by a weighting function,partitioned, overlapped, and added together. For example, if a narrowwindow is desired for an incoming wideband ERT signal, a window can beformed to only multiply the first N datapoints of the buffer while theother 3N points are multiplied by zeros (or very small numbers), 402,before partitioning, overlapping, adding, and passing through theN-point FFT. If a wide window is desired for a narrowband ERT signal, awindow can be formed to multiply the entire 4N datapoints, 406, of thebuffer before partitioning, overlapping, adding, and passing through theN-point FFT. Yet other windows can be formed to cover 2N data points ofthe buffer and multiply the rest by zeros or very small numbers, such asthat shown at 404.

According to this embodiment a fixed size input buffer (e.g. 4N) and afixed size FFT process (N-point FFT) is used to process a wide range ofbandwidths. In effect, this process can reduce any bandwidth by as muchas 4 fold. All it requires is to address a memory containing a newpre-calculated window function to multiply with the buffer entries. Dataoversampling may be considered to prevent problems such as aliasing.

FIG. 5 is a flow diagram of the proposed method in accordance with anembodiment of the present invention. At block 501 a data collectingunit, such as a DCU, receives the signal transmitted by a datatransmitting unit, such as an ERT. At block 502 the received signal issampled. At block 503 the sampled data enters into an input buffer; forexample an M×N-point input buffer, where N is the FFT process size and Mis an integer. At block 504 the buffer data content is multiplied by awindow (weighting) function which may contain (M−1)N, (M−2)N, . . . , or(M−M)N zeros or very small numbers reflecting the bandwidth. At block505 the multiplied data is parsed into M groups of N-point data. Atblock 506 the N-point data groups are combined together, such as beingadded together in a manner that: the 1st, (N+1)^(th), (2N+1)^(th), . . ., [(M−1)N+1)]^(th) points of the buffered data are added together and2^(nd), (N+2)^(th), (2N+2)^(th), . . . , [(M−1)N+2)]^(th) points areadded together and 3^(rd), (N+3)^(th), (2N+3)^(th), . . . ,[(M−1)N+3)]^(th) points are added together, up to and including N^(th),(N+N)^(th), (2N+N)^(th), . . . , [(M−1)N+N)]^(th) points of the buffereddata. And, at the block 507, the result of combining the segments ismathematically transformed to another domain, such as with an FFTprocess.

It is important to recognize that the different aspects of the presentinvention apply to both fixed and mobile receivers, and that the mentionof one does not exclude the other. An example of a fixed receiver is anAMR system mounted on an erected pole to facilitate the meter reading ofits surrounding utility customers.

Unless the context clearly requires otherwise, throughout thedescription and the claims, the words “comprise,” “comprising,” and thelike are to be construed in an inclusive sense, as opposed to anexclusive or exhaustive sense;

that is to say, in the sense of “including, but not limited to.”Additionally, the words “herein,” “above,” “below,” and words of similarimport, when used in this application, shall refer to this applicationas a whole and not to any particular portions of this application. Wherethe context permits, words in the above Detailed Description using thesingular or plural number may also include the plural or singular numberrespectively. When the claims use the word “or” in reference to a listof two or more items, that word covers all of the followinginterpretations of the word: any of the items in the list, all of theitems in the list, and any combination of the items in the list.

The above detailed description of embodiments of the invention is notintended to be exhaustive or to limit the invention to the precise formdisclosed above. While specific embodiments of, and examples for, theinvention are described above for illustrative purposes, variousequivalent modifications are possible within the scope of the invention,as those skilled in the relevant art will recognize. Also, the teachingsof the invention provided herein can be applied to other systems, notnecessarily the system described above. The elements and acts of thevarious embodiments described above can be combined to provide furtherembodiments.

All of the above patents and applications and other references,including any that may be listed in accompanying filing papers, areincorporated herein by reference. Aspects of the invention can bemodified, if necessary, to employ the systems, functions, and conceptsof the various references described above to provide yet furtherembodiments of the invention.

Changes can be made to the invention in light of the above “DetailedDescription.” While the above description details certain embodiments ofthe invention and describes the best mode contemplated, no matter howdetailed the above appears in text, the invention can be practiced inmany ways. Therefore, implementation details may vary considerably whilestill being encompassed by the invention disclosed herein. As notedabove, particular terminology used when describing certain features oraspects of the invention should not be taken to imply that theterminology is being redefined herein to be restricted to any specificcharacteristics, features, or aspects of the invention with which thatterminology is associated. In general, the terms used in the followingclaims should not be construed to limit the invention to the specificembodiments disclosed in the specification, unless the above DetailedDescription section explicitly defines such terms. Accordingly, theactual scope of the invention encompasses not only the disclosedembodiments, but also all equivalent ways of practicing or implementingthe invention under the claims. For example the invention is not limitedto AMR.

While certain aspects of the invention are presented below in certainclaim forms, the inventors contemplate the various aspects of theinvention in any number of claim forms. For example, while only oneaspect of the invention is recited as embodied in a computer-readablemedium, other aspects may likewise be embodied in a computer-readablemedium. Accordingly, the inventors reserve the right to add additionalclaims after filing the application to pursue such additional claimforms for other aspects of the invention.

1. In a utility meter reading system having multiple utility meterswirelessly transmitting utility meter data to a mobile or fixed wirelessreceiver, an adjustable bandwidth automated meter reading system,comprising: an encoder-receiver-transmitter (ERT) connected to each ofthe utility meters, wherein the ERT is configured to receive andwirelessly transmit utility metering data with respect to consumption ofat least one utility resource; and a mobile or fixed data collectionunit comprising a receiver and a signal processing resource, wherein thereceiver is configured to wirelessly receive the transmitted utilitymetering data, and wherein the signal processing resource is configuredfor performing N-point Fast Fourier Transformation (FFT), wherein thedata collection unit: stores the received data into an M×N long buffer,where M is an integer; multiplies the buffered utility meter data by awindow function, wherein the window function contains no zeros, onezero, or a plurality of zeros depending on how much the bandwidth is tobe adjusted; partitions the multiplied data into M equal segments, whereeach segment has N points; adds similarly positioned points of all thesegments together such that the most significant points of all the Msegments are added together, the second most significant points of allthe segments are added together, and likewise adds together othersimilarly situated points of the segments; and performs N-point FFT onthe N-point results of the additions to enable the adjustable bandwidthmeter reading system to carry out signal processing on narrow bandwidthdata to broadband data up to M×N points long.
 2. The adjustablebandwidth automated meter reading system of claim 1, wherein Nrepresents the widest bandwidth of the receiver.
 3. An adjustablebandwidth automated wireless utility meter reading system, comprising: atransmitter connected to the utility meter; and a receiver; wherein thereceiver includes an N-point Fast Fourier Transform (FFT) signalprocessing resource configured to: receive the utility meter dataprovided by the transmitter; store the received data into an M×N longbuffer; multiply the buffer data by a window function, wherein thewindow function contains no zeros, one zero, or a plurality of zerosdepending on how much the bandwidth is to be adjusted; partition themultiplied data into M equal segments, where each segment has N points;add similarly positioned points of all the segments together to form anN-point result, such that the 1^(st), (N+1)^(th), (2N+1)^(th), . . . ,[(M−1)N+1)]^(th) points of the buffered data are added together, the2^(nd), (N+2)^(th), (2N+2)^(th), . . . , [(M−1)N+2)]^(th) points areadded together, the 3^(rd), (N+3)^(th), (2N+3)^(th), . . . ,[(M−1)N+3)]^(th) points are added together, up to and including N^(th),(N+N)^(th), (2N+N)^(th), . . . , [(M−1)N+N)]^(th) points of the buffereddata; and perform N-point FFT on the N-point results of the additions,which enables the utility meter reading system to carry out signalprocessing on any data of up to M×N points long.
 4. A wireless utilitydata communication system for automatic utility meter reading, the datacommunication system comprising: a receiver for receiving encodedutility meter data; and a signal processing facility with a mathematicaltransformation capability, wherein the signal processing facility isconfigured or programmed to: read the received utility meter data into abuffer; mathematically manipulate the buffered utility meter data,wherein the mathematical manipulation comprises multiplication of thebuffer data by a weighting function; partition the manipulated utilitymeter data into segments; combine the segmented and partitioned utilitymeter data; and mathematically transform the combined utility meterdata.
 5. The wireless utility data communication system of claim 4,wherein the signal processing facility is a digital signal processor(DSP).
 6. The wireless utility data communication system of claim 4,wherein the mathematical transformation is an N-point Fast FourierTransform operation.
 7. (canceled)
 8. The wireless utility datacommunication system of claim 4, wherein the data buffer is M×N long andthe utility meter data is partitioned into M equal segments of N-pointdata, and wherein N represents the widest bandwidth of the receiver. 9.The wireless utility data communication system of claim 4, wherein thecombination of the partitioned data of the M segments comprise addingtogether similarly positioned points of all the M segments, such asadding the least significant points of all the segments together, andthe most significant points of all the segments together, and likewisethe other similarly situated points of all the segments.
 10. Thewireless utility data communication system of claim 4, wherein themathematical transformation of the combined data comprises a FourierTransform operation on the combined data.
 11. In a utility meter readingsystem having multiple utility meters wirelessly transmitting utilitymeter data to a wireless receiver, a combination of elements forproviding an adjustable bandwidth receiver comprising: a step forreceiving utility meter data from at least one of the multiple utilitymeters; a step for manipulating the received utility meter data; a stepfor parsing the manipulated data into segments; a step for combining thesegmented data; and a step for performing mathematical transformation onthe combined data, wherein the step for performing mathematicaltransformation on the combined data comprises performing Fast FourierTransform on the combined data.
 12. The combination of elements of claim11, wherein the step for manipulating the received utility meter datacomprises multiplying the data by a weighting function, and wherein thewindow function contains no zeros, one zero, or a plurality of zerosdepending on how much the bandwidth is to be adjusted.
 13. Thecombination of elements of claim 11, wherein the step for parsing themanipulated data into segments comprises dividing the data into M groupsof N-point data, wherein M is an integer and N represents the widestbandwidth of the receiver.
 14. The combination of elements of claim 11,wherein the step for combining the segmented data comprises addingtogether the similarly positioned bits of all the segments, such asadding the least significant bits of all the segments together, and themost significant bits of all the segments together, and likewise theother similarly situated points of all the segments.
 15. (canceled) 16.An adjustable bandwidth wireless data communication method for use withan automated utility meter data reading system, comprising: receivingthe utility meter data; storing the received utility meter data into abuffer; mathematically manipulating the stored data by multiplying thebuffer data with a weighting function; partitioning the manipulated datainto segments; combining the partitioned data by adding the partitioneddata together point-by-point; and mathematically transforming thecombined data through Fourier Transformation.
 17. The method of claim16, wherein the window function contains no zeros, one zero, or aplurality of zeros depending on how much the bandwidth is to beadjusted.
 18. The method of claim 16, wherein partitioning the data intosegments comprises dividing the data into M groups of N-point data,wherein M and N are integers.
 19. The method of claim 16, wherein addingthe partitioned data point-by-point comprises adding together thesimilarly positioned points of all the segments, such as adding theleast significant points of all the segments together, and the mostsignificant points of all the segments together, and likewise the othersimilarly situated points of the segments.
 20. The method of claim 16,wherein Fourier Transformation of the combined data comprises performingDiscrete Fourier Transformation on the combined data.
 21. A wirelessautomated utility meter data reading system, comprising: a means forreceiving the utility meter data; a means for storing the receivedutility meter data; a means for mathematically manipulating the storeddata, wherein the mathematical manipulation comprises multiplication ofthe stored data by a weighting function; a means for partitioning themanipulated data into segments; a means for combining the partitioneddata; and a means for mathematically transforming the combined data,wherein the means for mathematically transforming the combined datacomprises performing Fast Fourier Transform on the combined data.
 22. Anadjustable bandwidth wireless data communication method for use with anautomated utility meter data reading system, comprising: receiving theutility meter data; sampling or digitizing the received data storing thesampled or digitized data into an M×N long buffer; multiplying thebuffer data by a weighting function; partitioning the data into Mgroups, where each group includes N points; adding together thesimilarly positioned points of all the segments to form an N-pointresult, wherein each n^(th) point of the N-point result, where n=1, 2,3, . . . , N, is computed using:${\sum\limits_{m = 1}^{M}\left\lbrack {{\left( {m - 1} \right)N} + n} \right\rbrack};{and}$performing Fast Fourier Transformation on the N-point addition result.